Systems and methods for inventory reshuffling and rebalancing

ABSTRACT

A computer-implemented system and method for automated inventory using data associated with stock keeping unit SKU and fulfillment centers (FC) to initialize a data structure comprising a plurality of nodes, determine a weight associated with each FC based on the capacity of each FC, assignment SKU to one or more FCs, perform a preliminary mapping for the plurality of FCs, determining whether to rebalance the preliminary mapping of the quantity, and rebalancing the preliminary mapping based on the weights associated with each FC, to promote maximum utilization of the network.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. non-provisional applicationSer. No. 16/944,867, filed on Jul. 31, 2020. The disclosure of theabove-reference application is expressly incorporated herein byreference to its entirety.

TECHNICAL FIELD

The present disclosure generally relates to computerized methods andsystems for optimizing inventory management. In particular, embodimentsof the present disclosure relate to inventive and unconventionalcomputerized systems that rebalance incoming product orders, based oninformation associated with product SKUs, among a system of distributioncenters to maximize available distributive capacity while simultaneouslymaintaining various business requirements.

BACKGROUND

One major goal in the product delivery field is to minimize the timebetween when a product is purchased and when the product arrives at thepurchaser. Distribution centers for said product, therefore, should benumerous in number and advantageously located close to the potentialpurchasers, with a set amount of the product in stock ready forshipping. Such distribution centers, or fulfillment centers (FCs),processes millions of products daily as by fulfilling consumer orders assoon as the orders are placed and enable shipping carriers to pick upshipments. Operations for managing inventory inside FCs may includereceiving products from sellers, stocking the received products for easypicking access, packing the product, verifying the order, and deliveringthe product.

Although currently existing FCs and systems for inventory management inFCs are configured to handle large volumes of incoming and outgoingproducts, an issue arises when inventory of products are inefficientlydistributed among the network of FCs. For example, there may besituations in which certain FCs are near capacity in terms of storagespace or labor usage, while other FCs may have empty spaces orunder-utilized labor.

To mitigate such problems, conventional inventory management systemsrequire human intervention, that is for managers and workers to make adhoc decisions to shift products, (i.e. rebalancing inventory) among thenetwork of FCs, to either relieve congestion or better utilize capacity.Conventional methods are inefficient and labor intensive.

Therefore, there is a need for improved methods and systems forrebalancing the product inventory so that the network of FCs are fullyutilized.

SUMMARY

One aspect of the present disclosure is directed to acomputer-implemented system for automated inventory shuffling. Thesystem comprises at least one processor; a memory comprisinginstructions that, when executed by the at least one processor, performssteps comprising: receive information comprising data regarding anetwork of a plurality of fulfillment centers (FCs), the data comprisinga capacity of each FC; initialize a data structure comprising aplurality of nodes, the number of nodes equal to the number of FCs;determine, based on the capacity of each FC, a weight associated witheach FC relative to the received FC capacities; receive, for assignmentto one or more FCs, a product identifier associated with a product, theidentifier associated with a quantity and a minimum order quantity;perform a preliminary mapping of the quantity to the plurality of FCsbased on the associated minimum order quantity; based on the productidentifier, determining whether to rebalance the preliminary mapping ofthe quantity, and if so, rebalancing the preliminary mapping based onthe weights associated with each FC, to promote maximum utilization ofthe network; and forward instructions to a computer system to cause areceived quantity to be delivered to the network based on thepreliminary mapping.

Yet another aspect of the present disclosure is directed to acomputer-implemented method for inventory shuffling. The methodcomprises steps comprising: receive information comprising dataregarding a network of a plurality of fulfillment centers (FCs), thedata comprising a capacity of each FC; initialize a data structurecomprising a plurality of nodes, the number of nodes equal to the numberof FCs; determine, based on the capacity of each FC, a weight associatedwith each FC relative to the received FC capacities; receive, forassignment to one or more FCs, a product identifier associated with aproduct, the identifier associated with a quantity and a minimum orderquantity; perform a preliminary mapping of the quantity to the pluralityof FCs based on the associated minimum order quantity; based on theproduct identifier, determining whether to rebalance the preliminarymapping of the quantity, and if so, rebalancing the preliminary mappingbased on the weights associated with each FC, to promote maximumutilization of the network; and forward instructions to a computersystem to cause a received quantity to be delivered to the network basedon the preliminary.

Yet another aspect of the present disclosure is directed to acomputer-implemented method for inventory shuffling, the methodcomprising: receive information comprising data regarding a network of aplurality of fulfillment centers (FCs), the data comprising an inboundcapacity and a total capacity for each FC; initialize a data structurecomprising a plurality of nodes, the number of nodes equal to the numberof FCs; determine, based on a ratio of the inbound capacity and thetotal capacity, a utilization value each FC; receive, for assignment toone or more FCs, a product identifier associated with a product, theidentifier associated with a quantity and a minimum order quantity;perform a preliminary mapping of the quantity to the plurality of FCsbased on the associated minimum order quantity; based on the productidentifier, determining whether to rebalance the preliminary mapping ofthe quantity, and if so, rebalancing the preliminary mapping based onthe utilization value associated with each FC, to promote maximumutilization of the network; and forward instructions to a computersystem to cause a received quantity to be delivered to the network basedon the preliminary mapping.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a schematic block diagram illustrating an exemplaryembodiment of a network comprising computerized systems forcommunications enabling shipping, transportation, and logisticsoperations, consistent with the disclosed embodiments.

FIG. 1B depicts a sample Search Result Page (SRP) that includes one ormore search results satisfying a search request along with interactiveuser interface elements, consistent with the disclosed embodiments.

FIG. 1C depicts a sample Single Display Page (SDP) that includes aproduct and information about the product along with interactive userinterface elements, consistent with the disclosed embodiments.

FIG. 1D depicts a sample Cart page that includes items in a virtualshopping cart along with interactive user interface elements, consistentwith the disclosed embodiments.

FIG. 1E depicts a sample Order page that includes items from the virtualshopping cart along with information regarding purchase and shipping,along with interactive user interface elements, consistent with thedisclosed embodiments.

FIG. 2 is a diagrammatic illustration of an exemplary fulfillment centerconfigured to utilize disclosed computerized systems, consistent withthe disclosed embodiments.

FIG. 3 is a schematic block diagram illustrating an exemplary embodimentof a product attribute corresponding to a storage keeping unit (SKU),consistent with the disclosed embodiments.

FIG. 4 is a schematic block diagram illustrating an exemplary embodimentof a network of nodes corresponding to a network of Fulfillment Center(FCs), and an exemplary data node.

FIG. 5 is flow chart depicting an exemplary embodiment of a process formanaging product inventory across a network of FCs, consistent with thedisclosed embodiment.

FIG. 6 is a flow chart depicting an exemplary embodiment of a processfor rebalancing inventory for FCs based on product identifier.

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings.Wherever possible, the same reference numbers are used in the drawingsand the following description to refer to the same or similar parts.While several illustrative embodiments are described herein,modifications, adaptations and other implementations are possible. Forexample, substitutions, additions, or modifications may be made to thecomponents and steps illustrated in the drawings, and the illustrativemethods described herein may be modified by substituting, reordering,removing, or adding steps to the disclosed methods. Accordingly, thefollowing detailed description is not limited to the disclosedembodiments and examples. Instead, the proper scope of the invention isdefined by the appended claims.

Embodiments of the present disclosure are directed tocomputer-implemented systems and methods for optimizing productinventory by rebalancing a quantities of products destined forfulfillment centers. The disclosed embodiments provide innovativetechnical features that allow for automated inventory rebalancing byleveraging SKU based inventory management technology and networkinfrastructure to dynamically rebalance an order quantity to achieveoptimal inventory level, taking into account real-time businessinformation and constraints. For example, the disclosed embodimentsenable efficient assignment of inventory level for a product across anetwork of fulfillment centers, re-outing of incoming shipment of theproduct to a specific fulfillment center (FC), and adjusting orderquantity for restocking orders.

Referring to FIG. 1A, a schematic block diagram 100 illustrating anexemplary embodiment of a system comprising computerized systems forcommunications enabling shipping, transportation, and logisticsoperations is shown. As illustrated in FIG. 1A, system 100 may include avariety of systems, each of which may be connected to one another viaone or more networks. The systems may also be connected to one anothervia a direct connection, for example, using a cable. The depictedsystems include a shipment authority technology (SAT) system 101, anexternal front end system 103, an internal front end system 105, atransportation system 107, mobile devices 107A, 107B, and 107C, sellerportal 109, shipment and order tracking (SOT) system 111, fulfillmentoptimization (FO) system 113, fulfillment messaging gateway (FMG) 115,supply chain management (SCM) system 117, warehouse management system119, mobile devices 119A, 119B, and 119C (depicted as being inside offulfillment center (FC) 200), 3^(rd) party fulfillment systems 121A,121B, and 121C, fulfillment center authorization system (FC Auth) 123,and labor management system (LMS) 125.

SAT system 101, in some embodiments, may be implemented as a computersystem that monitors order status and delivery status. For example, SATsystem 101 may determine whether an order is past its Promised DeliveryDate (PDD) and may take appropriate action, including initiating a neworder, reshipping the items in the non-delivered order, canceling thenon-delivered order, initiating contact with the ordering customer, orthe like. SAT system 101 may also monitor other data, including output(such as a number of packages shipped during a particular time period)and input (such as the number of empty cardboard boxes received for usein shipping). SAT system 101 may also act as a gateway between differentdevices in system 100, enabling communication (e.g., usingstore-and-forward or other techniques) between devices such as externalfront end system 103 and FO system 113.

External front end system 103, in some embodiments, may be implementedas a computer system that enables external users to interact with one ormore systems in system 100. For example, in embodiments where system 100enables the presentation of systems to enable users to place an orderfor an item, external front end system 103 may be implemented as a webserver that receives search requests, presents item pages, and solicitspayment information. For example, external front end system 103 may beimplemented as a computer or computers running software such as theApache HTTP Server, Microsoft Internet Information Services (IIS),NGINX, or the like. In other embodiments, external front end system 103may run custom web server software designed to receive and processrequests from external devices (e.g., mobile device 102A or computer102B), acquire information from databases and other data stores based onthose requests, and provide responses to the received requests based onacquired information.

In some embodiments, external front end system 103 may include one ormore of a web caching system, a database, a search system, or a paymentsystem. In one aspect, external front end system 103 may comprise one ormore of these systems, while in another aspect, external front endsystem 103 may comprise interfaces (e.g., server-to-server,database-to-database, or other network connections) connected to one ormore of these systems.

An illustrative set of steps, illustrated by FIGS. 1B, 1C, 1D, and 1E,will help to describe some operations of external front end system 103.External front end system 103 may receive information from systems ordevices in system 100 for presentation and/or display. For example,external front end system 103 may host or provide one or more web pages,including a Search Result Page (SRP) (e.g., FIG. 1B), a Single DetailPage (SDP) (e.g., FIG. 1C), a Cart page (e.g., FIG. 1D), or an Orderpage (e.g., FIG. 1E). A user device (e.g., using mobile device 102A orcomputer 102B) may navigate to external front end system 103 and requesta search by entering information into a search box. External front endsystem 103 may request information from one or more systems in system100. For example, external front end system 103 may request informationfrom FO System 113 that satisfies the search request. External front endsystem 103 may also request and receive (from FO System 113) a PromisedDelivery Date or “PDD” for each product included in the search results.The PDD, in some embodiments, may represent an estimate of when apackage containing the product will arrive at the user's desiredlocation or a date by which the product is promised to be delivered atthe user's desired location if ordered within a particular period oftime, for example, by the end of the day (11:59 PM). (PDD is discussedfurther below with respect to FO System 113.)

External front end system 103 may prepare an SRP (e.g., FIG. 1B) basedon the information. The SRP may include information that satisfies thesearch request. For example, this may include pictures of products thatsatisfy the search request. The SRP may also include respective pricesfor each product, or information relating to enhanced delivery optionsfor each product, PDD, weight, size, offers, discounts, or the like.External front end system 103 may send the SRP to the requesting userdevice (e.g., via a network).

A user device may then select a product from the SRP, e.g., by clickingor tapping a user interface, or using another input device, to select aproduct represented on the SRP. The user device may formulate a requestfor information on the selected product and send it to external frontend system 103. In response, external front end system 103 may requestinformation related to the selected product. For example, theinformation may include additional information beyond that presented fora product on the respective SRP. This could include, for example, shelflife, country of origin, weight, size, number of items in package,handling instructions, or other information about the product. Theinformation could also include recommendations for similar products(based on, for example, big data and/or machine learning analysis ofcustomers who bought this product and at least one other product),answers to frequently asked questions, reviews from customers,manufacturer information, pictures, or the like.

External front end system 103 may prepare an SDP (Single Detail Page)(e.g., FIG. 1C) based on the received product information. The SDP mayalso include other interactive elements such as a “Buy Now” button, a“Add to Cart” button, a quantity field, a picture of the item, or thelike. The SDP may further include a list of sellers that offer theproduct. The list may be ordered based on the price each seller offerssuch that the seller that offers to sell the product at the lowest pricemay be listed at the top. The list may also be ordered based on theseller ranking such that the highest ranked seller may be listed at thetop. The seller ranking may be formulated based on multiple factors,including, for example, the seller's past track record of meeting apromised PDD. External front end system 103 may deliver the SDP to therequesting user device (e.g., via a network).

The requesting user device may receive the SDP which lists the productinformation. Upon receiving the SDP, the user device may then interactwith the SDP. For example, a user of the requesting user device mayclick or otherwise interact with a “Place in Cart” button on the SDP.This adds the product to a shopping cart associated with the user. Theuser device may transmit this request to add the product to the shoppingcart to external front end system 103.

External front end system 103 may generate a Cart page (e.g., FIG. 1D).The Cart page, in some embodiments, lists the products that the user hasadded to a virtual “shopping cart.” A user device may request the Cartpage by clicking on or otherwise interacting with an icon on the SRP,SDP, or other pages. The Cart page may, in some embodiments, list allproducts that the user has added to the shopping cart, as well asinformation about the products in the cart such as a quantity of eachproduct, a price for each product per item, a price for each productbased on an associated quantity, information regarding PDD, a deliverymethod, a shipping cost, user interface elements for modifying theproducts in the shopping cart (e.g., deletion or modification of aquantity), options for ordering other product or setting up periodicdelivery of products, options for setting up interest payments, userinterface elements for proceeding to purchase, or the like. A user at auser device may click on or otherwise interact with a user interfaceelement (e.g., a button that reads “Buy Now”) to initiate the purchaseof the product in the shopping cart. Upon doing so, the user device maytransmit this request to initiate the purchase to external front endsystem 103.

External front end system 103 may generate an Order page (e.g., FIG. 1E)in response to receiving the request to initiate a purchase. The Orderpage, in some embodiments, re-lists the items from the shopping cart andrequests input of payment and shipping information. For example, theOrder page may include a section requesting information about thepurchaser of the items in the shopping cart (e.g., name, address, e-mailaddress, phone number), information about the recipient (e.g., name,address, phone number, delivery information), shipping information(e.g., speed/method of delivery and/or pickup), payment information(e.g., credit card, bank transfer, check, stored credit), user interfaceelements to request a cash receipt (e.g., for tax purposes), or thelike. External front end system 103 may send the Order page to the userdevice.

The user device may enter information on the Order page and click orotherwise interact with a user interface element that sends theinformation to external front end system 103. From there, external frontend system 103 may send the information to different systems in system100 to enable the creation and processing of a new order with theproducts in the shopping cart.

In some embodiments, external front end system 103 may be furtherconfigured to enable sellers to transmit and receive informationrelating to orders.

Internal front end system 105, in some embodiments, may be implementedas a computer system that enables internal users (e.g., employees of anorganization that owns, operates, or leases system 100) to interact withone or more systems in system 100. For example, in embodiments wherenetwork 101 enables the presentation of systems to enable users to placean order for an item, internal front end system 105 may be implementedas a web server that enables internal users to view diagnostic andstatistical information about orders, modify item information, or reviewstatistics relating to orders. For example, internal front end system105 may be implemented as a computer or computers running software suchas the Apache HTTP Server, Microsoft Internet Information Services(IIS), NGINX, or the like. In other embodiments, internal front endsystem 105 may run custom web server software designed to receive andprocess requests from systems or devices depicted in system 100 (as wellas other devices not depicted), acquire information from databases andother data stores based on those requests, and provide responses to thereceived requests based on acquired information.

In some embodiments, internal front end system 105 may include one ormore of a web caching system, a database, a search system, a paymentsystem, an analytics system, an order monitoring system, or the like. Inone aspect, internal front end system 105 may comprise one or more ofthese systems, while in another aspect, internal front end system 105may comprise interfaces (e.g., server-to-server, database-to-database,or other network connections) connected to one or more of these systems.

Transportation system 107, in some embodiments, may be implemented as acomputer system that enables communication between systems or devices insystem 100 and mobile devices 107A-107C. Transportation system 107, insome embodiments, may receive information from one or more mobiledevices 107A-107C (e.g., mobile phones, smart phones, PDAs, or thelike). For example, in some embodiments, mobile devices 107A-107C maycomprise devices operated by delivery workers. The delivery workers, whomay be permanent, temporary, or shift employees, may utilize mobiledevices 107A-107C to effect delivery of packages containing the productsordered by users. For example, to deliver a package, the delivery workermay receive a notification on a mobile device indicating which packageto deliver and where to deliver it. Upon arriving at the deliverylocation, the delivery worker may locate the package (e.g., in the backof a truck or in a crate of packages), scan or otherwise capture dataassociated with an identifier on the package (e.g., a barcode, an image,a text string, an RFID tag, or the like) using the mobile device, anddeliver the package (e.g., by leaving it at a front door, leaving itwith a security guard, handing it to the recipient, or the like). Insome embodiments, the delivery worker may capture photo(s) of thepackage and/or may obtain a signature using the mobile device. Themobile device may send information to transportation system 107including information about the delivery, including, for example, time,date, GPS location, photo(s), an identifier associated with the deliveryworker, an identifier associated with the mobile device, or the like.Transportation system 107 may store this information in a database (notpictured) for access by other systems in system 100. Transportationsystem 107 may, in some embodiments, use this information to prepare andsend tracking data to other systems indicating the location of aparticular package.

In some embodiments, certain users may use one kind of mobile device(e.g., permanent workers may use a specialized PDA with custom hardwaresuch as a barcode scanner, stylus, and other devices) while other usersmay use other kinds of mobile devices (e.g., temporary or shift workersmay utilize off-the-shelf mobile phones and/or smartphones).

In some embodiments, transportation system 107 may associate a user witheach device. For example, transportation system 107 may store anassociation between a user (represented by, e.g., a user identifier, anemployee identifier, or a phone number) and a mobile device (representedby, e.g., an International Mobile Equipment Identity (IMEI), anInternational Mobile Subscription Identifier (IMSI), a phone number, aUniversal Unique Identifier (UUID), or a Globally Unique Identifier(GUID)). Transportation system 107 may use this association inconjunction with data received on deliveries to analyze data stored inthe database in order to determine, among other things, a location ofthe worker, an efficiency of the worker, or a speed of the worker.

Seller portal 109, in some embodiments, may be implemented as a computersystem that enables sellers or other external entities to electronicallycommunicate with one or more systems in system 100. For example, aseller may utilize a computer system (not pictured) to upload or provideproduct information, order information, contact information, or thelike, for products that the seller wishes to sell through system 100using seller portal 109.

Shipment and order tracking system 111, in some embodiments, may beimplemented as a computer system that receives, stores, and forwardsinformation regarding the location of packages containing productsordered by customers (e.g., by a user using devices 102A-102B). In someembodiments, shipment and order tracking system 111 may request or storeinformation from web servers (not pictured) operated by shippingcompanies that deliver packages containing products ordered bycustomers.

In some embodiments, shipment and order tracking system 111 may requestand store information from systems depicted in system 100. For example,shipment and order tracking system 111 may request information fromtransportation system 107. As discussed above, transportation system 107may receive information from one or more mobile devices 107A-107C (e.g.,mobile phones, smart phones, PDAs, or the like) that are associated withone or more of a user (e.g., a delivery worker) or a vehicle (e.g., adelivery truck). In some embodiments, shipment and order tracking system111 may also request information from warehouse management system (WMS)119 to determine the location of individual products inside of afulfillment center (e.g., fulfillment center 200). Shipment and ordertracking system 111 may request data from one or more of transportationsystem 107 or WMS 119, process it, and present it to a device (e.g.,user devices 102A and 102B) upon request.

Fulfillment optimization (FO) system 113, in some embodiments, may beimplemented as a computer system that stores information for customerorders from other systems (e.g., external front end system 103 and/orshipment and order tracking system 111). FO system 113 may also storeinformation describing where particular items are held or stored. Forexample, certain items may be stored only in one fulfillment center,while certain other items may be stored in multiple fulfillment centers.In still other embodiments, certain fulfilment centers may be designedto store only a particular set of items (e.g., fresh produce or frozenproducts). FO system 113 stores this information as well as associatedinformation (e.g., quantity, size, date of receipt, expiration date,etc.).

FO system 113 may also calculate a corresponding PDD (promised deliverydate) for each product. The PDD, in some embodiments, may be based onone or more factors. For example, FO system 113 may calculate a PDD fora product based on a past demand for a product (e.g., how many timesthat product was ordered during a period of time), an expected demandfor a product (e.g., how many customers are forecast to order theproduct during an upcoming period of time), a network-wide past demandindicating how many products were ordered during a period of time, anetwork-wide expected demand indicating how many products are expectedto be ordered during an upcoming period of time, one or more counts ofthe product stored in each fulfillment center 200, which fulfillmentcenter stores each product, expected or current orders for that product,or the like.

In some embodiments, FO system 113 may determine a PDD for each producton a periodic basis (e.g., hourly) and store it in a database forretrieval or sending to other systems (e.g., external front end system103, SAT system 101, shipment and order tracking system 111). In otherembodiments, FO system 113 may receive electronic requests from one ormore systems (e.g., external front end system 103, SAT system 101,shipment and order tracking system 111) and calculate the PDD on demand.

Fulfilment messaging gateway (FMG) 115, in some embodiments, may beimplemented as a computer system that receives a request or response inone format or protocol from one or more systems in system 100, such asFO system 113, converts it to another format or protocol, and forward itin the converted format or protocol to other systems, such as WMS 119 or3^(rd) party fulfillment systems 121A, 121B, or 121C, and vice versa.

Supply chain management (SCM) system 117, in some embodiments, may beimplemented as a computer system that performs forecasting functions.For example, SCM system 117 may forecast a level of demand for aparticular product based on, for example, based on a past demand forproducts, an expected demand for a product, a network-wide past demand,a network-wide expected demand, a count products stored in eachfulfillment center 200, expected or current orders for each product, orthe like. In response to this forecasted level and the amount of eachproduct across all fulfillment centers, SCM system 117 may generate oneor more purchase orders to purchase and stock a sufficient quantity tosatisfy the forecasted demand for a particular product.

Warehouse management system (WMS) 119, in some embodiments, may beimplemented as a computer system that monitors workflow. For example,WMS 119 may receive event data from individual devices (e.g., devices107A-107C or 119A-119C) indicating discrete events. For example, WMS 119may receive event data indicating the use of one of these devices toscan a package. As discussed below with respect to fulfillment center200 and FIG. 2 , during the fulfillment process, a package identifier(e.g., a barcode or RFID tag data) may be scanned or read by machines atparticular stages (e.g., automated or handheld barcode scanners, RFIDreaders, high-speed cameras, devices such as tablet 119A, mobiledevice/PDA 119B, computer 119C, or the like). WMS 119 may store eachevent indicating a scan or a read of a package identifier in acorresponding database (not pictured) along with the package identifier,a time, date, location, user identifier, or other information, and mayprovide this information to other systems (e.g., shipment and ordertracking system 111).

WMS 119, in some embodiments, may store information associating one ormore devices (e.g., devices 107A-107C or 119A-119C) with one or moreusers associated with system 100. For example, in some situations, auser (such as a part- or full-time employee) may be associated with amobile device in that the user owns the mobile device (e.g., the mobiledevice is a smartphone). In other situations, a user may be associatedwith a mobile device in that the user is temporarily in custody of themobile device (e.g., the user checked the mobile device out at the startof the day, will use it during the day, and will return it at the end ofthe day).

WMS 119, in some embodiments, may maintain a work log for each userassociated with system 100. For example, WMS 119 may store informationassociated with each employee, including any assigned processes (e.g.,unloading trucks, picking items from a pick zone, rebin wall work,packing items), a user identifier, a location (e.g., a floor or zone ina fulfillment center 200), a number of units moved through the system bythe employee (e.g., number of items picked, number of items packed), anidentifier associated with a device (e.g., devices 119A-119C), or thelike. In some embodiments, WMS 119 may receive check-in and check-outinformation from a timekeeping system, such as a timekeeping systemoperated on a device 119A-119C.

3^(rd) party fulfillment (3PL) systems 121A-121C, in some embodiments,represent computer systems associated with third-party providers oflogistics and products. For example, while some products are stored infulfillment center 200 (as discussed below with respect to FIG. 2 ),other products may be stored off-site, may be produced on demand, or maybe otherwise unavailable for storage in fulfillment center 200. 3PLsystems 121A-121C may be configured to receive orders from FO system 113(e.g., through FMG 115) and may provide products and/or services (e.g.,delivery or installation) to customers directly. In some embodiments,one or more of 3PL systems 121A-121C may be part of system 100, while inother embodiments, one or more of 3PL systems 121A-121C may be outsideof system 100 (e.g., owned or operated by a third-party provider).

Fulfillment Center Auth system (FC Auth) 123, in some embodiments, maybe implemented as a computer system with a variety of functions. Forexample, in some embodiments, FC Auth 123 may act as a single-sign on(SSO) service for one or more other systems in system 100. For example,FC Auth 123 may enable a user to log in via internal front end system105, determine that the user has similar privileges to access resourcesat shipment and order tracking system 111, and enable the user to accessthose privileges without requiring a second log in process. FC Auth 123,in other embodiments, may enable users (e.g., employees) to associatethemselves with a particular task. For example, some employees may nothave an electronic device (such as devices 119A-119C) and may insteadmove from task to task, and zone to zone, within a fulfillment center200, during the course of a day. FC Auth 123 may be configured to enablethose employees to indicate what task they are performing and what zonethey are in at different times of day.

Labor management system (LMS) 125, in some embodiments, may beimplemented as a computer system that stores attendance and overtimeinformation for employees (including full-time and part-time employees).For example, LMS 125 may receive information from FC Auth 123, WMA 119,devices 119A-119C, transportation system 107, and/or devices 107A-107C.

The particular configuration depicted in FIG. 1A is an example only. Forexample, while FIG. 1A depicts FC Auth system 123 connected to FO system113, not all embodiments require this particular configuration. Indeed,in some embodiments, the systems in system 100 may be connected to oneanother through one or more public or private networks, including theInternet, an Intranet, a WAN (Wide-Area Network), a MAN(Metropolitan-Area Network), a wireless network compliant with the IEEE802.11a/b/g/n Standards, a leased line, or the like. In someembodiments, one or more of the systems in system 100 may be implementedas one or more virtual servers implemented at a data center, serverfarm, or the like.

FIG. 2 depicts a fulfillment center 200. Fulfillment center 200 is anexample of a physical location that stores items for shipping tocustomers when ordered. Fulfillment center (FC) 200 may be divided intomultiple zones, each of which are depicted in FIG. 2 . These “zones,” insome embodiments, may be thought of as virtual divisions betweendifferent stages of a process of receiving items, storing the items,retrieving the items, and shipping the items. So while the “zones” aredepicted in FIG. 2 , other divisions of zones are possible, and thezones in FIG. 2 may be omitted, duplicated, or modified in someembodiments.

Inbound zone 203 represents an area of FC 200 where items are receivedfrom sellers who wish to sell products using system 100 from FIG. 1A.For example, a seller may deliver items 202A and 202B using truck 201.Item 202A may represent a single item large enough to occupy its ownshipping pallet, while item 202B may represent a set of items that arestacked together on the same pallet to save space.

A worker will receive the items in inbound zone 203 and may optionallycheck the items for damage and correctness using a computer system (notpictured). For example, the worker may use a computer system to comparethe quantity of items 202A and 202B to an ordered quantity of items. Ifthe quantity does not match, that worker may refuse one or more of items202A or 202B. If the quantity does match, the worker may move thoseitems (using, e.g., a dolly, a handtruck, a forklift, or manually) tobuffer zone 205. Buffer zone 205 may be a temporary storage area foritems that are not currently needed in the picking zone, for example,because there is a high enough quantity of that item in the picking zoneto satisfy forecasted demand. In some embodiments, forklifts 206 operateto move items around buffer zone 205 and between inbound zone 203 anddrop zone 207. If there is a need for items 202A or 202B in the pickingzone (e.g., because of forecasted demand), a forklift may move items202A or 202B to drop zone 207.

Drop zone 207 may be an area of FC 200 that stores items before they aremoved to picking zone 209. A worker assigned to the picking task (a“picker”) may approach items 202A and 202B in the picking zone, scan abarcode for the picking zone, and scan barcodes associated with items202A and 202B using a mobile device (e.g., device 119B). The picker maythen take the item to picking zone 209 (e.g., by placing it on a cart orcarrying it).

Picking zone 209 may be an area of FC 200 where items 208 are stored onstorage units 210. In some embodiments, storage units 210 may compriseone or more of physical shelving, bookshelves, boxes, totes,refrigerators, freezers, cold stores, or the like. In some embodiments,picking zone 209 may be organized into multiple floors. In someembodiments, workers or machines may move items into picking zone 209 inmultiple ways, including, for example, a forklift, an elevator, aconveyor belt, a cart, a handtruck, a dolly, an automated robot ordevice, or manually. For example, a picker may place items 202A and 202Bon a handtruck or cart in drop zone 207 and walk items 202A and 202B topicking zone 209.

A picker may receive an instruction to place (or “stow”) the items inparticular spots in picking zone 209, such as a particular space on astorage unit 210. For example, a picker may scan item 202A using amobile device (e.g., device 119B). The device may indicate where thepicker should stow item 202A, for example, using a system that indicatean aisle, shelf, and location. The device may then prompt the picker toscan a barcode at that location before stowing item 202A in thatlocation. The device may send (e.g., via a wireless network) data to acomputer system such as WMS 119 in FIG. 1A indicating that item 202A hasbeen stowed at the location by the user using device 119B.

Once a user places an order, a picker may receive an instruction ondevice 119B to retrieve one or more items 208 from storage unit 210. Thepicker may retrieve item 208, scan a barcode on item 208, and place iton transport mechanism 214. While transport mechanism 214 is representedas a slide, in some embodiments, transport mechanism may be implementedas one or more of a conveyor belt, an elevator, a cart, a forklift, ahandtruck, a dolly, a cart, or the like. Item 208 may then arrive atpacking zone 211.

Packing zone 211 may be an area of FC 200 where items are received frompicking zone 209 and packed into boxes or bags for eventual shipping tocustomers. In packing zone 211, a worker assigned to receiving items (a“rebin worker”) will receive item 208 from picking zone 209 anddetermine what order it corresponds to. For example, the rebin workermay use a device, such as computer 119C, to scan a barcode on item 208.Computer 119C may indicate visually which order item 208 is associatedwith. This may include, for example, a space or “cell” on a wall 216that corresponds to an order. Once the order is complete (e.g., becausethe cell contains all items for the order), the rebin worker mayindicate to a packing worker (or “packer”) that the order is complete.The packer may retrieve the items from the cell and place them in a boxor bag for shipping. The packer may then send the box or bag to a hubzone 213, e.g., via forklift, cart, dolly, handtruck, conveyor belt,manually, or otherwise.

Hub zone 213 may be an area of FC 200 that receives all boxes or bags(“packages”) from packing zone 211. Workers and/or machines in hub zone213 may retrieve package 218 and determine which portion of a deliveryarea each package is intended to go to, and route the package to anappropriate camp zone 215. For example, if the delivery area has twosmaller sub-areas, packages will go to one of two camp zones 215. Insome embodiments, a worker or machine may scan a package (e.g., usingone of devices 119A-119C) to determine its eventual destination. Routingthe package to camp zone 215 may comprise, for example, determining aportion of a geographical area that the package is destined for (e.g.,based on a postal code) and determining a camp zone 215 associated withthe portion of the geographical area.

Camp zone 215, in some embodiments, may comprise one or more buildings,one or more physical spaces, or one or more areas, where packages arereceived from hub zone 213 for sorting into routes and/or sub-routes. Insome embodiments, camp zone 215 is physically separate from FC 200 whilein other embodiments camp zone 215 may form a part of FC 200.

Workers and/or machines in camp zone 215 may determine which routeand/or sub-route a package 220 should be associated with, for example,based on a comparison of the destination to an existing route and/orsub-route, a calculation of workload for each route and/or sub-route,the time of day, a shipping method, the cost to ship the package 220, aPDD associated with the items in package 220, or the like. In someembodiments, a worker or machine may scan a package (e.g., using one ofdevices 119A-119C) to determine its eventual destination. Once package220 is assigned to a particular route and/or sub-route, a worker and/ormachine may move package 220 to be shipped. In exemplary FIG. 2 , campzone 215 includes a truck 222, a car 226, and delivery workers 224A and224B. In some embodiments, truck 222 may be driven by delivery worker224A, where delivery worker 224A is a full-time employee that deliverspackages for FC 200 and truck 222 is owned, leased, or operated by thesame company that owns, leases, or operates FC 200. In some embodiments,car 226 may be driven by delivery worker 224B, where delivery worker224B is a “flex” or occasional worker that is delivering on an as-neededbasis (e.g., seasonally). Car 226 may be owned, leased, or operated bydelivery worker 224B.

FIG. 3 is a schematic block diagram illustrating an exemplary embodimenta product attribute corresponding to a storage (or stock) keeping unit(SKU), consistent with the disclosed embodiments. Product attribute maycontain information regarding a particular product, which may include,but not limited to manufacturer, description, material, size, color,packaging, quantity in inventory, quantity ordered, demand level (e.g.,velocity), expiration, etc. In some embodiments, a SKU 300 is associatedwith product attribute 310 and barcode 302, barcode 302 being linked toproduct attribute 310. Barcode 302 may be placed on the product itself,on the product's packaging, or on tags or attachment affixed to theproduct or its packaging. Barcode 302 is configured to be readable orscannable by a barcode reader or scanner, not illustrated. In someembodiments, mobile devices 107A-C may possess imaging components suchas a camera, and therefore may function as barcode readers or scanners.An ordinary skilled person will appreciate that barcode 302 is anon-limiting example of an automatic identification and data capture(AIDC) scheme that may be implemented consistent with the disclosureembodiments. For example, instead of, or in addition to a barcode, SKU300 may be linked to a QR code, a RFID tag, magnetic strip or any otherAIDC.

Product attribute 310, which is associated with SKU 300, is linked tobarcode 302. Product attribute 310 may be stored in databases and bemanipulated by any computer systems. In the exemplary embodiment,product attribute 310 is stored in FO system 113, and may be accessed byany of the interconnected systems illustrated in FIG. 1A. For example, aworker using a mobile device 107A may access product attribute 310 byscanning barcode 302, or other input means, and obtain productinformation associated with SKU 300. Similarly, the worker may edit orupdate product information when, for example, a quantity of the productis delivered or received. Additionally, or alternatively, productattribute 310 may be accessed by SOT system 111, transportation system107, SCM system 117 or other systems as whenever the product informationis needed or updated.

In the exemplary embodiment, product attribute 310 comprises at leastdata regarding a minimum reorder quantity (MOQ) 311, a safety reorderquantity (SOQ) 312, a cycle reorder quantity (COQ) 313, an inventoryquantity 314, a product band (Band) 315, and a node assignment 316 ofthe particular product. One of ordinary skill will appreciate that thedata listed herein are non-limiting, and product attribute 310 maycontain other data concerning the particular product.

MOQ 311 represents a fixed quantity of the particular product that isordered whenever a fulfillment center (FC) restocks the particularproduct. For example, if a FC replenishes its stock of widget A, therestocking order must contain an amount of widget A greater than orequal to MOQ 311.

SOQ 312 represents a quantity of the particular product that should beordered, for a specific FC, such that its inventory quantity 314 is keptabove a desired number. For example, if a FC replenishes its stock ofwidget A, the restocking order should contain an amount of widget Agreater than or equal to SOQ 312 for widget A, such that the specific FCwill be sufficiently stocked with widget A before the nextreplenishment.

COQ 313 represents a quantity of the particular product that could beordered, for a specific FC, for any business reasons. For example, if aFC replenishes its stock of widget A, the restocking order could containan amount of widget equal to COQ 313. COQ 313 may be adjusted to scalewith expected demand or to hedge against price fluctuation, or otherbusiness or operational reasons.

Inventory quantity 314 represents a quantity of the particular productthat is currently stocked at a specific FC, across the entire network ofFCs, or both. For example, inventory quantity 314 may keep tracks ofwidget A by tracking a quantity of widget A across all FCs, as well as aquantity of widget A in fulfillment center A (FC A), a quantity ofwidget A in FC B, and so forth.

Band 315 represents one or more groups into which SKU 300 associatedwith the particular product is assigned. In some embodiments, thegrouping may be based on a relative ranking of sales quantity of theparticular product. For example, widget A may be assigned to group 1because widget A is a highly demanded product, while widget B isassigned to group 2 because widget B is in low demand. One of ordinaryskill will understand that the embodiments described are non-limiting;for example, widgets may be assigned to more groups. Moreover, otherparallel grouping of products may be employed to group and sort productsfor other reasons.

Node assignment 316 represents rules limiting a quantities of theparticular product at a FC. For example, it may be desirable for widgetA to be only stocked at designated FCs, or that widget A be preventedfrom being stocked at designated FCs.

FIG. 4 is a schematic block diagram illustrating an exemplary embodimentof a network of nodes corresponding to a network of fulfillment center(FCs), and an individual exemplary data node.

In the exemplary embodiments, a plurality of fulfillment centers (FCs)form a network of fulfilment centers (FC network) 401. In someembodiments, each FC within the FC network may correspond to FC 200illustrated in FIG. 2 , described in detail in previous sections.

In the exemplary embodiments, a plurality of data nodes, hereafterreferred to as nodes, forms a network of nodes (node network) 402. Thenodes may be a structured in a hub-and-spoke configuration, with everynode connected to each other through a central hub. In the exemplaryembodiment, each node 410 corresponds to a FC, thus the number of nodesin node network 402 is equal to the number of FCs in FC network 401. Forexample, Node 1 corresponds to FC1, Node 2 correspond to FC2, and soforth. Node 410 is a data structure that may contain any and all datarelating the corresponding FC. In the exemplary embodiment, node 410comprises at least one or more product identifiers 411 corresponding toone or more products stocked in a FC, capacity 412 of a FC, weightingfactor 413 assigned to a FC, and cost value 414 assigned a FC. One ofordinary skill will appreciate that the information contained in node410 are not limited to the ones listed, and that node 410 may containother data relating to a FC.

In the exemplary embodiment, node 410 is stored in FO system 113, andmay be accessed by any of the interconnected systems illustrated in FIG.1A. Additionally, or alternatively, node 410 may be accessed by SOTsystem 111, transportation system 107, SCM system 117 or other systemswhenever information regarding a FC is needed or updated.

Product identifiers 411 may be a collection of a plurality of individualSKUs 300 corresponding to the products at are stocked at the specificFC. For example, if 50 different products are stocked at the specificFC, product identifiers 411 will contain 50 individual SKUs 300, as wellall information regarding the product that is contained within SKU 300as illustrated in FIG. 3 and previously described.

Capacity 412 represents a capability of the specific FC to operate. Forexample, capacity 412 may be a quantity of products that can be stockedby the FC, a quantity of products that can be received by the FC, or aquantity of products that can be delivered from the FC. In someembodiments, capacity 412 of the FC may be limited by availability oftotal storage space, warehouse workers, delivery workers, deliveryvehicles, and so forth. In some embodiments, capacity 412 may be productspecific. For example, node 410 may have one capacity for widget A, anda different capability for widget B. One of ordinary skill willappreciate that differences between products, such as ones betweentoilet papers and TV sets, will result in a FC having different valuesof capacity 412 for the different products. In some embodiments, thenumbers of different capacity values correspond to the numbers ofdifferent SKUs 300 in the product identifier 411. In some embodiments, aFC may have height limit due to structural constraint, and would thushave limited capacity to handle oversized products. In some embodiments,a FC may have limited refrigeration capacity, and would thus havelimited capacity to handle items that require refrigeration or freezing.

In some embodiments, capacity 412 for a specific FC may be dynamic. Forexample, capacity 412 for the FC may vary based on a quantity ofproducts currently stocked at the FC. Higher quantity may mean highutilization of storage space, hence a lower value for capacity 412.Additionally, or alternatively, capacity 412 may vary with demand forproducts. For example, capacity 412 for the FC may vary based on aquantity of product that is predicted to arrive at or leave from the FC.Higher quantity may mean that high utilization of workers and equipment,hence a lower value for capacity 412.

Weighting factor 413 represents a numerical value associated a specificnode 410, corresponding to a particular FC. Weighting factor 413 may becalculated using various input values such as capacity 412 and productidentifier 411. For example, for each product at each node, an expectedutilization may be determined based on a current capacity and anincoming quantity. In some embodiments, the incoming capacity may be oneof MOQ 311, SOQ 312, or COQ 313, and the current capacity may bedetermined by capacity 412. If, for example, the expected utilization isbelow a threshold value at node 410, weighting factors may be leftunchanged (i.e. node 410 will receive the incoming quantity). If, forexample, the expected utilization is above the threshold for node 410,weighting factor 413 may be lowered for node 410 such that the productis directed to a different node having the next lowest expectedutilization. This may be applicable to products that are always in highdemand for all FCs, and thus no re-shuffling is needed even if capacityacross the node network 402 may vary. In some embodiments, the thresholdvalue may be related to band 315, and product in high a demand band maybe assigned higher threshold value. Additionally or alternatively, if aproduct is not in high demand, weighting factor 413 may be adjusted sothat the product is routed to a different node having the next lowestexpected utilization, without regard to the threshold value.

Cost value 414 represents a numerical value associated with a specificnode 410, corresponding to a particular FC. Cost value 414 may beobtained from a cost function. In some embodiment, the threshold valueused to determine the weighting factor 413 may be the cost value.

FIG. 5 is flow chart depicting an exemplary embodiment of a process 500for managing a particular product inventory having an SKUs 300 across anetwork of FCs, consistent with the disclosed embodiments. In theexemplary embodiment, FO system 113 may carry out process 500.Additionally, or alternatively, SOT system 111, transportation system107, SCM system 117 and/or other systems illustrated in FIG. 1A maycarry out all or part of process 500.

In step 501, FO system 113 receive data relating to a plurality of FCs200. In some embodiments, FO system 113 may obtain pre-existing datafrom known databases. These pre-existing data may be stored in FO system113, SOT system 111, transportation system 107, SCM system 117 or othersystems or databases connected to FO system 113. These pre-existing datamay contain information such as inventory of product stocked in each FC200, SKU 300 associated with the inventory of products, number ofworkers and equipment, or other similarly relevant information. In someembodiments, data relating to a plurality of FCs 200 may be accessedfrom SKU 300. For example, by accessing SKUs 300, FO system 113 mayobtain, for different products, values such as MOQ 311, SOQ 312, COQ313, inventory quantity 314, band 315 and node assignment 316.

In step 502, from these obtained pre-existing data, FO system 113 maycreate node network 402, comprising a plurality of nodes 410, eachcorresponding to a specific FC 200. Alternatively, node network 402 mayalready exist within FO system 113, and only updates of relevant data isneeded in step 502. Additionally or alternatively, in step 502, FOsystem 113 may create a new node within node network 402 if a new FC isestablished. Similarly, FO system 113 may delete a node from nodenetwork 402 if an existing FC is decommissioned.

In step 503, FO system 113 determines weighting factor 413 for each node410. Weighting factor 413 is determined based on capacity 412 andinventory quantity of the particular product. In some embodiment,capacity 412 comprises an inbound capacity. The inbound capacityrepresents the ability of the specific FC 200 to receive the particularproduct, measured in quantity of product. The inbound capacity may belimited by the number of workers or equipment available to unload andstock the product, or inbound labor capacity. The inbound capacity of aproduct may be affected by the inbound capacity of another product, asthe two products may compete with each other for the same labor hour. Insome embodiments, the inbound capacity may also depend on the totalstorage space of the specific FC for the particular product, or inboundspace capacity, so the inbound capacity may be the minimum of theinbound labor capacity and the inbound storage capacity.

In some embodiments, weighting factor 413 may be determined by scaling avalue determined by a difference between the inbound capacity and theinventory level for the particular product, such that a FC having ahigher inbound capacity and a lower inventory quantity would have ahigher weight factor. For example, if FC1 and FC2 both have a inboundcapacity of receiving 1000 unit of widget A each, but FC1 has aninventory of 0 widget A in stock, while FC2 has an inventory of 500widget A in stock, FC1 would have a higher weighting factor than FC2since the difference between the inbound capacity and the inventorylevel is greater for FC1 than for FC2.

In step 504, FO system 113 performs a preliminary mapping of each SKU300 to each node 410. For example, FO system 113 directs restockingorders of each product to individual FCs. FO system 113 may contain aset of rules governing mapping of each SKU 300 to each node 410. Therules may be extensive and takes into account many properties ofproducts and FCs. For example, during preliminary mapping, MOQ 311, SOQ312, or COQ 313 may be calculated for every node in node network 402 tomaintain enough inventory until the next ordering cycle.

In some embodiments, rules for preliminary mapping comprises determiningvalues of SOQ 312 and COQ 313, based on values of MOQ 311, for each node410 in node network 402. In the exemplary embodiments, MOQ 311 isgenerally fixed for a particular product, since it may represents aminimum quantity for bulk order. MOQ 311 is generally constrained byoutside factors and cannot be easily adjusted. Therefore, it may not bepossible to stock the particular product to an exact unit numberdesired. In some embodiments, SOQ 312 is determined by historical data.For example, widget A may have an order cycle of 2 weeks, and FC1 hashistorically delivered on average 100 units of widget A during any 2week period. Thus FO system 113 may determine that SOQ 312 of widget Afor FC1 should be around 100. Similarly, FO system 113 may determine COQ313 based on historical data. For example, FO system 113 may determinethat during particular times in a year, FC1 delivers 150 widget A. ThusFO system 113 may determine that COQ 313 should be 50 for thatparticular time of year. These historical data may be stored on orretrieved from any one of the systems illustrated in FIG. 1A, such asSOT system 111, transportation system 107, FO system 113 or SCM system117. Taking into account SOQ 312, COQ 313, and MOQ 311, FO system 113directs restocking orders of the particular product (i.e. maps SKU 300)to the individual FC 200.

In step 505, FO system 113 makes a determination on whether arebalancing of the inventory is required for a particular product. Insome embodiments, FO system 113 makes this determination based on band315 associated with SKU 300 of the particular product, which will bedescribed in further detail below with reference to FIG. 6 .Additionally, or alternatively, FO system 113 may make thisdetermination based on node assignment 316 of SKU 300 associated withthe particular product. For example, if node assignment 316 designatethat the particular product is only stocked at a specific FC, then thereis no need to rebalance the inventory of the product among other FCs.

If FO system 113 determines that a rebalancing is required, FO system113 remaps SKUs 300 to nodes 410 in step 506, based on weighting factor413 for the individual nodes across the entire node network 402. There-mapping is similar to step 504, but with the additional considerationof weighting factor 413. For example, using weighting factors calculatedin step 503, if FO system 113 determines that for a particular product,FC1 has a greater weighting factor value then FC2, FO system 113 wouldcalculate a rebalanced value of SOQ 312, COQ 313, or both, for FC1 andFC2. The rebalanced values are such that for FC1, the rebalanced valuesof SOQ 312 or COQ 313 would be greater than values of SOQ 312 or COQ 313initially calculated in step 504. Similarly, the rebalanced values aresuch that for FC2, the rebalanced values of SOQ 312 or COQ 313 would beless than values of SOQ 312 or COQ 313 initially calculated in step 504.Thus, the quantity of restocking order would be adjusted higher for FCswith higher capacity in relations to inventory level for a particularproduct, and adjusted lower for FCs with lower capacity in relations toinventory level. One of ordinary skill will appreciate that the examplegiven is non-limiting, and that other factors are taken intoconsideration, such as the various rules described in step 504.

Once remapping is completed in step 506, or if FO system 113 determinesthat rebalancing is not required, FO system 113 executes the mapping,and the orders for stocking of products at FCs are carried out in step507.

In some alternative embodiments, in additions to calculating andassigning a weighting factor 413, FO system 113 calculate cost value 414associated with a specific FC across the node network 402 for aparticular product. For example, in step 503, cost values 414 may becalculated and assigned to individual nodes 410 in addition to weightingfactor 413.

In some alternative embodiments of step 503, FO system 113 receivescapacity 412 for node 410 associated with a specific FC 200. Aspreviously discussed, capacity 412 may comprise an inbound capacity forthe specific FC. Capacity 412 may further comprise a total capacity. FOsystem 113 determines a FC utilization value based on the ratio of theinbound capacity and the total capacity for the FC. FO system 113 alsoreceives an inbound order quantity in step 503. The inbound orderquantity is total quantity of a particular product (associated with SKU300) that is due to arrive across the entire node network 402. FO system113 also receives a reorder quantity of the particular product(associated with SKU 300) for a specific node 410 in node network 402.In some embodiments, the reorder quantity may be the sum of SOQ 312 andCOQ 313. As discussed above, values of SOQ 312 and COQ 313 may be basedon historical values or projections.

FO system 113 may calculate cost value 414 based on an inventory factorand a FC utilization factor. In some embodiments, FO system 113 derivesthe inventory factor based on a quantity of SKU present at FC(Inv_(FC)), a quantity of SKU assigned to FC (Inv_(AS)) by system 113, atotal quantity of SKU (Inv_(TO)) across node network 402, and thereorder quantity (ROQ). In some embodiments, the inventory factor may begiven as:

$C_{1}\frac{{Inv}_{FC} + {Inv}_{AS}}{{Inv}_{TO} + {ROQ}}$

C₁ being the first scaling factor. In some embodiments, FO system 113derives the FC utilization factor by scaling the FC utilization value(Utili_(FC)) by a second scaling factor C₂. In some embodiments, costvalue 414 may be the sum of the inventory factor and the FC utilizationfactor, given as:

${{Cost}\mspace{14mu}{Value}} = {{C_{1}\frac{{Inv}_{FC} + {Inv}_{AS}}{{Inv}_{TO} + {ROQ}}} + {C_{2} \cdot {Utili}_{FC}}}$

In some embodiments, the first scaling factor and the second scalingfactor may be adjusted from time to time to achieve a cost value 414that optimize inventory shuffling across FCs. One of ordinary skill willappreciate that cost value 414 obtained will be lower for FCs with highreorder quantity and low FC utilization value, thus it may beadvantageous to direct a higher quantity of the particular product toFCs with lower cost value 414. FO system 113 assigns cost value 414 toindividual node 410 in alternative step 503.

In some alternative embodiments of step 506, FO system 113 remaps SKUs300 to nodes 410 based on cost value 414 for the individual nodes acrossthe entire node network 402.

FIG. 6 is a flow chart depicting an exemplary embodiment of a processfor rebalancing inventory for FCs based on product attribute 310 of aparticular product. In some embodiment, product attribute 310 isassociated SKU 300. Process 600 corresponds to step 505 of process 500.Process 600 categorizes products based on product attribute 310associated with SKU 300. FO system 113 determines a priority forrebalancing inventory based on the category of the products.

In step 601, FO system 113 receives SKU 300 associated with theparticular product. As previously discussed, SKU 300 contains data suchas Inventory Quantity 314 and Band 315.

In step 602, FO system 113 determines a demand for the product. Thedemand for the product can be determined based on band 315. For example,products in the system may be sorted based on total quantity delivered.This sorting may be performed by FO system 113, SOT system 111,transportation system 107, SCM system 117 or other systems illustratedin FIG. 1A. Based on the sorting, products and their associated SKUs 300may be assigned into different bands, such as Band₁, Band₂ . . .Band_(n). Band 315 identifies which band SKU 300 belongs to. In someembodiments, the number of bands may be arbitrary and can be altered asneeded. For example, the top 20% of products delivered may be placed inBand1, the next 20% in Band2, and so forth.

In step 603, FO system 113 assign SKU 300 of the particular product intocategories. In some embodiments, the categories are 1) Rebalance Needed,and 2) Rebalance Unneeded. The assignment of categories may be based onband 315 of SKU 300. For example, FO system 113 may determine that onlyhighly demanded products require inventory rebalancing. Therefore, theonly products having band 315 that falls within Band₁ is assigned to theRebalance Needed category, while all other SKUs are assigned to theRebalance Unneeded category. Alternatively, in another non-limitingexample, if only very low demand products are exempted from inventoryrebalancing, then FO system 113 assigns products having band 315 thatfalls within Band₁, Band₂, Band₃, or Band₄ to Rebalance Needed category,while only Band₅ is assigned Rebalance Unneeded category. One ofordinary skill will appreciate that the number of bands, criteria foreach band, and threshold for the categories described above are mereillustrative examples, and these values can be adjusted based on needsthat arise.

In step 604, FO system 113 checks SKU 300 associated with the particularproduct for which category the product has been assigned. If thecategory is 1, FO system 113 proceeds to step 605, which corresponds to“YES” designation in step 505. If the category is 2, FO system 113proceeds to step 606, which corresponds to “NO” designation in step 505.

While the present disclosure has been shown and described with referenceto particular embodiments thereof, it will be understood that thepresent disclosure can be practiced, without modification, in otherenvironments. The foregoing description has been presented for purposesof illustration. It is not exhaustive and is not limited to the preciseforms or embodiments disclosed. Modifications and adaptations will beapparent to those skilled in the art from consideration of thespecification and practice of the disclosed embodiments. Additionally,although aspects of the disclosed embodiments are described as beingstored in memory, one skilled in the art will appreciate that theseaspects can also be stored on other types of computer readable media,such as secondary storage devices, for example, hard disks or CD ROM, orother forms of RAM or ROM, USB media, DVD, Blu-ray, or other opticaldrive media.

Computer programs based on the written description and disclosed methodsare within the skill of an experienced developer. Various programs orprogram modules can be created using any of the techniques known to oneskilled in the art or can be designed in connection with existingsoftware. For example, program sections or program modules can bedesigned in or by means of .Net Framework, .Net Compact Framework (andrelated languages, such as Visual Basic, C, etc.), Java, C++,Objective-C, HTML, HTML/AJAX combinations, XML, or HTML with includedJava applets.

Moreover, while illustrative embodiments have been described herein, thescope of any and all embodiments having equivalent elements,modifications, omissions, combinations (e.g., of aspects across variousembodiments), adaptations and/or alterations as would be appreciated bythose skilled in the art based on the present disclosure. Thelimitations in the claims are to be interpreted broadly based on thelanguage employed in the claims and not limited to examples described inthe present specification or during the prosecution of the application.The examples are to be construed as non-exclusive. Furthermore, thesteps of the disclosed methods may be modified in any manner, includingby reordering steps and/or inserting or deleting steps. It is intended,therefore, that the specification and examples be considered asillustrative only, with a true scope and spirit being indicated by thefollowing claims and their full scope of equivalents.

What is claimed is:
 1. A computer-implemented system for automatedinventory shuffling, comprising: at least one processor; a memorycomprising instructions that, when executed by the at least oneprocessor, performs steps comprising: receive information comprisingdata regarding a network of a plurality of fulfillment centers (FCs) inone format or protocol, the data comprising a capacity of each FC;convert the received information into another format or protocol; basedon the converted information, initialize a data structure comprising aplurality of nodes, the plurality of nodes corresponding to theplurality of FCs; determine, based on the capacity of each FC, aweighting factor associated with each FC relative to the received FCcapacities, wherein the weighting factor is associated with an inboundcapacity of the respective FC and an inventory level in the respectiveFC; receive, for assignment to one or more FCs, a product identifierassociated with a product, the identifier associated with a firstquantity and a minimum order quantity, wherein the product identifiersare divided into one or more categories by: receiving informationassociated with a plurality of product identifiers, the informationcomprising demand of each product identifier; assigning a plurality ofsubsets of the product identifiers with highest demand forecastquantities to a first set of categories; and assigning the remainingsubsets of the product identifiers with the next highest demand forecastquantities to a second set of categories; perform a preliminary mappingof the first quantity to the plurality of FCs based on the associatedminimum order quantity; determine a category associated with the productidentifier; based on determining that the product identifier isassociated with the first set of categories, rebalance the preliminarymapping of the first quantity, wherein rebalancing the preliminarymapping comprises: adjusting the data structure comprising the pluralityof nodes to reassign the first quantity to the plurality of FCs based onthe weighting factor associated with each of the plurality of FCs;receive data associated with a second quantity to be delivered to thenetwork of the plurality of FCs in one format or protocol; convert thereceived data into another format or protocol; and based on theconverted data and the rebalanced preliminary mapping, cause the secondquantity to be delivered to the network of the plurality of FCs.
 2. Thecomputer-implemented system of claim 1, wherein: the first quantitycomprises at least a safety reorder quantity and a cycle reorderquantity; and rebalancing the preliminary mapping of the first quantityfurther comprises rebalancing the safety reorder quantity across thenetwork of the plurality of FCs.
 3. The computer-implemented system ofclaim 1, wherein: the first quantity comprises at least a safety reorderquantity and a band associated with relative ranking of sales quantity;and rebalancing the preliminary mapping of the first quantity furthercomprises rebalancing the safety reorder quantity across the network ofthe plurality of FCs.
 4. The computer-implemented system of claim 1,wherein: the number of nodes is equal to the number of FCs.
 5. Thecomputer-implemented system of claim 1, wherein the first quantity ofthe product identifier comprises at least one of a sum of demandforecast quantities for the product over a first period of time and asum of safety stock quantities for the product over a second period oftime.
 6. The computer-implemented system of claim 1, wherein the firstquantity of the product identifier is determined based on a number ofincoming orders for the associated product.
 7. The computer-implementedsystem of claim 2, wherein the cycle reorder quantity is adjusted withexpected demand.
 8. The computer-implemented system of claim 1, whereinrebalancing the preliminary mapping further comprises evaluating a costfunction for each FC.
 9. The computer-implemented system of claim 8,wherein the cost function comprises determining a cost value for each FCbased on the first quantity associated with the product identifier, areorder quantity associated with the product identifier, and an FCutilization value.
 10. The computer-implemented system of claim 9,wherein the steps further comprise assigning a higher proportion of thefirst quantity to an FC having a lowest associated cost value.
 11. Acomputer-implemented method for inventory shuffling, the method beingperformed by at least one processor executing stored instructions toperform steps comprising: receiving information comprising dataregarding a network of a plurality of fulfillment centers (FCs) in oneformat or protocol, the data comprising a capacity of each FC;converting the received information into another format or protocol;based on the converted information, initializing a data structurecomprising a plurality of nodes, the plurality of nodes corresponding tothe plurality of FCs; determining, based on the capacity of each FC, aweighting factor associated with each FC relative to the received FCcapacities, wherein the weighting factor is associated with an inboundcapacity of the respective FC and an inventory level in the respectiveFC; receiving, for assignment to one or more FCs, a product identifierassociated with a product, the identifier associated with a firstquantity and a minimum order quantity, wherein the product identifiersare divided into one or more categories by: receiving informationassociated with a plurality of product identifiers, the informationcomprising demand of each product identifier; assigning a plurality ofsubsets of the product identifiers with highest demand forecastquantities to a first set of categories; and assigning the remainingsubsets of the product identifiers with the next highest demand forecastquantities to a second set of categories; and performing a preliminarymapping of the first quantity to the plurality of FCs based on theassociated minimum order quantity; determining a category associatedwith the product identifier; based on determining that the productidentifier is associated with the first set of categories, rebalancingthe preliminary mapping of the first quantity, wherein rebalancing thepreliminary mapping comprises: adjusting the data structure comprisingthe plurality of nodes to reassign the first quantity to the pluralityof FCs based on the weighting factor associated with each of theplurality of FCs; receiving data associated with a second quantity to bedelivered to the network of the plurality of FCs in one format orprotocol; converting the received data into another format or protocol;and based on the converted data and the rebalanced preliminary mapping,causing the second quantity to be delivered to the network of theplurality of FCs.
 12. The computer-implemented method of claim 11,wherein: the first quantity comprises at least a safety reorder quantityand a cycle reorder quantity; and rebalancing the preliminary mapping ofthe first quantity further comprises rebalancing the safety reorderquantity across the network of the plurality of FCs.
 13. Thecomputer-implemented method of claim 11, wherein: the first quantitycomprises at least a safety reorder quantity and a band associated withrelative ranking of sales quantity; and rebalancing the preliminarymapping of the first quantity further comprises rebalancing the safetyreorder quantity across the network of the plurality of FCs.
 14. Thecomputer-implemented method of claim 11, wherein: the number of nodes isequal to the number of FCs.
 15. The computer-implemented method of claim11, wherein the first quantity of the product identifier comprises atleast one of a sum of demand forecast quantities for the product over afirst period of time and a sum of safety stock quantities for theproduct over a second period of time.
 16. The computer-implementedmethod of claim 11, wherein the first quantity of the product identifieris determined based on a number of incoming orders for the associatedproduct.
 17. The computer-implemented method of claim 12, wherein thecycle reorder quantity is adjusted with expected demand.
 18. Thecomputer-implemented method of claim 11, wherein rebalancing thepreliminary mapping further comprises evaluating a cost function foreach FC.
 19. The computer-implemented method of claim 18, wherein thesteps further comprise assigning a higher proportion of the firstquantity to an FC having a lowest associated cost value.
 20. Acomputer-implemented method inventory shuffling, the method beingperformed by at least one processor of a networked server executingstored instructions to perform steps comprising: receiving informationcomprising data regarding a network of a plurality of fulfillmentcenters (FCs) in one format or protocol, the data comprising an inboundcapacity and a total capacity of each FC; converting the receivedinformation into another format or protocol; based on the convertedinformation, initializing a data structure comprising a plurality ofnodes, the plurality of nodes corresponding to the plurality of FCs,wherein the number of nodes is equal to the number of FCs; determining,based on a ratio of the inbound capacity and the total capacity, autilization value for each FC; receiving, for assignment to one or moreFCs, a product identifier associated with a product, the identifierassociated with a first quantity and a minimum order quantity, whereinthe product identifiers are divided into one or more categories by:receiving information associated with a plurality of product identifierswith highest demand forecast quantities to a first set of categoriesand; assigning the remaining subsets of the product identifiers with thenext highest demand forecast quantities to a second set of categoriesand; performing a preliminary mapping of the first quantity to theplurality of FCs based on the associated minimum order quantity;determining a category associated with the product identifier; based ondetermining that the product identifier is associated with a first setof categories, rebalancing the preliminary mapping of the first quantitybased on the utilization value associated with each FC, whereinrebalancing the preliminary mapping comprises: evaluating a costfunction for each FC; and adjusting the data structure comprising theplurality of nodes to reassign the first quantity to the plurality ofFCs based on the weighting factor associated with each of the pluralityof FCs and the cost function for each FC; receiving data associated witha second quantity to be delivered to the network of the plurality of FCsin one format or protocol; converting the received data into anotherformat or protocol; and based on the converted data and the rebalancedpreliminary mapping, causing a second quantity to be delivered to thenetwork of the plurality of FCs.